Effort Aversion and Reward Sensitivity in Schizophrenia: Computational Phenotyping of Motivational Deficits across Behavioral Tasks

精神分裂症患者的努力厌恶和奖赏敏感性:跨行为任务的动机缺陷的计算表型分析

阅读:1

Abstract

BACKGROUND: Motivational deficits have a major impact on the quality of life of patients with schizophrenia (SCZ) and respond poorly to antipsychotic medication. However, the underlying mechanisms, which cannot be accessed through conventional questionnaire-based scoring, remain largely unknown. This study aims to identify dysfunctional mechanisms that generate motivation deficits in patients with SCZ. STUDY DESIGN: Behavioral tests were combined with computational modeling to elucidate motivational deficits in 35 patients with SCZ compared to 35 matched healthy controls (HC). All participants performed a comprehensive set of behavioral tasks, including preference tasks in which participants rated and chose between various hypothetical effort costs and expected outcomes (rewards or punishments), and performance tasks in which they adjusted motor or cognitive effort production to the outcome at stake. STUDY RESULTS: Preference tasks (likability ratings and binary choices) revealed a significantly greater aversion to hypothetical effort costs in patients relative to HC, with no significant difference in the sensitivity to reward or punishment. Performance tasks (grip and Stroop) confirmed a greater aversion to cognitive effort (but not motor effort), and additionally uncovered a lower sensitivity to expected outcomes (both rewards and punishments). CONCLUSIONS: In contrast to what was observed in other clinical populations, results were not consistent across behavioral tasks. The observed pattern highlights the complexity of motivational deficits in patients with SCZ, which may not be reducible to a single underlying mechanism. The most consistent finding was an increased aversion to cognitive effort, which may underlie the apathy manifested by most patients with SCZ.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。